The Internet is a rapidly developing source of information useful to consumers in planning their activities and travel. Weather and climate information are of particular interest in this planning. Unfortunately, the Internet sites that provide weather and climate information have generally focused on providing short term weather forecast information and have limited content for longer-term planning. Furthermore, consumers generally have to go through several layers of navigation before reaching information that is useful for planning purposes. For more information on the deficiencies of some current weather information services see U.S. patent application Ser. No. 09/766,295 to Ryan, et al. entitled “Weather Information Delivery Systems and Methods Providing Planning Functionality And Navigation Tools” published as U.S. Patent Application 20020130899 and U.S. patent application Ser. No. 09/707,335 entitled “Targeted Weather Information Delivery Systems and Methods;” now abandoned, both incorporated herein by this reference.
Weather and climate have a great influence on people's activity and travel planning. People rely on weather forecast and climate information when making decisions and planning their activities and often wonder and discuss the optimal times to do certain things (e.g., play golf, visit a particular city, plant trees or flowers). They frequently ask questions such as what is the best time to visit Colorado, what is the best time of year to vacation in Kingston, Jamaica, are conditions good for a vacation to Cancun, etc. Unfortunately, there is no comprehensive source that provides objectively based answers to these questions.
Guide books, almanacs, and travel planning guides may offer recommendations about the best and worst times of year to visit an area and may even mention times of the year that are better for certain activities, such as golf, than other times of year. One of the problems with these recommendations is that they are typically vague and have a high level of subjectivity. Furthermore, the recommendation information does not take into account the consumer's specific preferences. For example, one person may prefer playing golf in hot weather rather than cool weather, while another prefers playing in cool weather rather than hot weather, while yet another is relatively indifferent to the temperature as long as its within a certain range but is more sensitive to and does not enjoy playing in windy conditions.
Weather forecast information available on the Internet may also be useful in planning activities. However, this type of information is typically based on short term weather forecasts. Weather forecast based activity indexes currently provide activity specific information based mostly on short term forecasted weather conditions, such as a 10-day forecast. For example, golf indexes are available as a measure of a set of weather conditions that influence the game of golf, such as temperature, humidity, lightning conditions, wind conditions, and precipitation. This allows consumers to more easily plan their activities by giving consumers the short term forecasted weather information tightly integrated with golf information.
Weather forecasts typically involve very limited climate information. Climate information may be used as a check to tell when short term forecasts are far off. Typical forecasts are based on ground observations of current and recent weather conditions such as dew point, humidity, visibility, cloud cover, etc. Weather forecasts are also based in part on current and recent weather balloon data. Typically, weather forecasting systems combine the ground and weather balloon observation data in a computer model to create a weather forecast. This is done for multiple locations around the globe and forecasts are typically combined together to create a model of the global flow of weather around the planet. These forecast models are usually run and rerun four or five times a day to ensure that the information in the model is current. These weather forecasting and modeling techniques provide useful weather information for short term activity planning.
In spite of the many uses and benefits of the weather-based activity planning tools available, there continues to be a need for additional and more powerful activity planning functionality. Specifically, consumers desire a tool that can help them make longer term planning decisions based on climate data as well as other factors. Climate data, which is typically based on historical data, is useful in understanding expected weather conditions for a given location. Climate data is often important for making long term and more general predictions about the weather conditions. For example, some sources of climate data provide data for a set 30 year period, allowing predictions to be made about future years, e.g. the fact that the average temperature in Atlanta in August over a recent 30 years period was 92 degrees can be used to predict that next August in Atlanta will have daily temperatures somewhere around 92 degrees. Climate data is typically collected and maintained in 30 year sets of data and updated every ten years rather than on a rolling period. For example, some sources of climate data are currently using a data set that includes information compiled from 1970 to 2000. Thirty years of relatively recent data is typically enough to provide reliable averages but does not extend so far back that global shifts in climate skew the results. Generally, the dataset of climate data should encompass a range of years that is broad enough that it provides a representative picture of what usually happens and current enough to reflect recent climatology shifts.
Current planning systems and tools do not allow users to conveniently and easily see how climate data impacts activity planning. There is currently no source of weather information that provides a comprehensive tool for long term planning based on more general climate data. Accordingly, there is a need for a comprehensive source to provide climate-based activity and travel planning.